machine-learning

Small scale machine learning projects to understand the core concepts . Give a Star 🌟If it helps you. BONUS: Interview Bank coming up..!

TabICLv2: An open tabular foundation model

Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).

Guia de referências técnicas para carreira em dados

Survival analysis built on top of scikit-learn

LLMs as Copilots for Theorem Proving in Lean

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

Arm NN ML Software.

Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)

A curated list of the most impressive AI papers

Highly Performant, Modular, Memory Safe and Production-ready Inference, Ingestion and Indexing built in Rust 🦀

Hopsworks - Data-Intensive AI platform with a Feature Store

High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.

Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

Hypernetworks that adapt LLMs for specific benchmark tasks using only textual task description as the input

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

Convolutional neural network for analyzing pentest screenshots

🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.

Fast citation reference parsing

Instructional notebooks on music information retrieval.

:basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.

Therapeutics Commons (TDC): Multimodal Foundation for Therapeutic Science

Scalable machine 🤖 learning for time series forecasting.

Pruna is a model optimization framework built for developers, enabling you to deliver faster, more efficient models with minimal overhead.

Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces

Interactively explore unstructured datasets from your dataframe.

Paper reading notes on Deep Learning and Machine Learning

GraphVite: A General and High-performance Graph Embedding System

A simple and well styled PPO implementation. Based on my Medium series: https://medium.com/@eyyu/coding-ppo-from-scratch-with-pytorch-part-1-4-613dfc1b14c8.

Resources to learn AI